Ecosystem resilience despite large-scale altered hydroclimatic conditions.

Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (1975-1998), and drier, warmer conditions in the early twenty-first century (2000-2009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUE(e): above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUE(e) in drier years that increased significantly with drought to a maximum WUE(e) across all biomes; and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century drought--that is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUE(e) may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands.

Long-term agroecosystem research in the central Mississippi river basin: goodwater creek experimental watershed flow data.

Flow monitoring in Goodwater Creek Experimental Watershed started in 1971 at three nested watersheds ranging from 12 to 73 km. Since then, runoff or stream flow has been measured at 14 plots, three fields, and 12 additional stream sites ranging from 0.0034 to 6067 km in the Central Mississippi River Basin. Long-term data sets are important to document the changes resulting from anthropogenic and natural drivers. The data set presented here documents discharge across a range of catchment sizes in an area known for its high runoff potential. It constitutes the flow database of the Central Mississippi River Basin site of the Long-Term Agricultural Research network. Like the other sites of this network, data are accessible through the STEWARDS web interface (). Here we (i) describe the data collection methods, (ii) document the data available at plot, field, and watershed scales, and (iii) provide the main characteristics of discharge. General characteristics of discharge per unit area for different cropping system management systems show that in this claypan soil setting, management and tillage of row crop systems do not affect surface flow during the growing season (April-October). Data from fields and stream sites show the dampening of peak flow values and lengthening of storm hydrographs caused by mixed land uses and longer times of concentration. Overall, stream flow accounts for a third of the precipitation, of which 80% is from surface runoff and 20% is from groundwater.

Long-term agroecosystem research in the central Mississippi river basin: hyperspectral remote sensing of reservoir water quality.

In situ methods for estimating water quality parameters would facilitate efforts in spatial and temporal monitoring, and optical reflectance sensing has shown potential in this regard, particularly for chlorophyll, suspended sediment, and turbidity. The objective of this research was to develop and evaluate relationships between hyperspectral remote sensing and lake water quality parameters-chlorophyll, turbidity, and N and P species. Proximal hyperspectral water reflectance data were obtained on seven sampling dates for multiple arms of Mark Twain Lake, a large man-made reservoir in northeastern Missouri. Aerial hyperspectral data were also obtained on two dates. Water samples were collected and analyzed in the laboratory for chlorophyll, nutrients, and turbidity. Previously reported reflectance indices and full-spectrum (i.e., partial least squares regression) methods were used to develop relationships between spectral and water quality data. With the exception of dissolved NH, all measured water quality parameters were strongly related ( ≥ 0.7) to proximal reflectance across all measurement dates. Aerial hyperspectral sensing was somewhat less accurate than proximal sensing for the two measurement dates where both were obtained. Although full-spectrum calibrations were more accurate for chlorophyll and turbidity than results from previously reported models, those previous models performed better for an independent test set. Because extrapolation of estimation models to dates other than those used to calibrate the model greatly increased estimation error for some parameters, collection of calibration samples at each sensing date would be required for the most accurate remote sensing estimates of water quality.

Long-term agroecosystem research in the central Mississippi river basin: goodwater creek experimental watershed weather data.

Knowledge of weather, particularly precipitation, is fundamental to interpreting watershed and hydrologic processes. The long-term weather record in the Goodwater Creek Experimental Watershed (GCEW) complements hydrologic and water quality data in the region. The GCEW also is the core of the Central Mississippi River Basin (CMRB) node of the Long-Term Agroecosystem Research network. Our objectives are to (i) describe the climatological context of the GCEW and CMRB settings, (ii) document instrumentation and the data collection, quality assurance, and reduction processes; (iii) provide examples of the data obtained and descriptive statistics; and (iv) document the availability of and access methods to obtain the data from the web-based data access portal at . These objectives support an overall goal to make these long-term data available to the public for use in further analyses and modeling in support of research and public policy on watershed management.

Long-term agroecosystem research in the central Mississippi river basin: introduction, establishment, and overview.

Many challenges currently facing agriculture require long-term data on landscape-scale hydrologic responses to weather, such as from the Goodwater Creek Experimental Watershed (GCEW), located in northeastern Missouri, USA. This watershed is prone to surface runoff despite shallow slopes, as a result of a significant smectitic clay layer 30 to 50 cm deep that restricts downward flow of water and gives rise to a periodic perched water table. This paper is the first in a series that documents the database developed from GCEW. The objectives of this paper are to (i) establish the context of long-term data and the federal infrastructure that provides it, (ii) describe the GCEW/ Central Mississippi River Basin (CMRB) establishment and the geophysical and anthropogenic context, (iii) summarize in brief the collected research results published using data from within GCEW, (iv) describe the series of papers this work introduces, and (v) identify knowledge gaps and research needs. The rationale for the collection derives from converging trends in data from long-term research, integration of multiple disciplines, and increasing public awareness of increasingly larger problems. The outcome of those trends includes being selected as the CMRB site in the USDA-ARS Long-Term Agro-Ecosystem Research (LTAR) network. Research needs include quantifying watershed scale fluxes of N, P, K, sediment, and energy, accounting for fluxes involving forest, livestock, and anthropogenic sources, scaling from near-term point-scale results to increasingly long and broad scales, and considering whole-system interactions. This special section informs the scientific community about this database and provides support for its future use in research to solve natural resource problems important to US agricultural, environmental, and science policy.